Product
Feature
Quick Research
Generate reliable direction feasibility study reports for your R&D in just a few steps.
Technical Q&A
Discover and master advanced knowledge NOW. Basics, ideas, possibilities, all at once.
Find Solutions
As an expert in R&D theories, this can generate solutions to your technical problems instantly.
Evaluate Feasibility
Analyze your overall solution with one click, know your potential R&D risks in advance.
Monitor Landscape
Get weekly tech updates, stay abreast of the latest tech innovations and key insights.
Patents
Literature
Hiro is an intelligent assistant for R&D personnel, combined with Patent DNA, to facilitate innovative research.
80 results about "Grid clustering" patented technology
Efficacy Topic
Property
Owner
Technical Advancement
Application Domain
Technology Topic
Technology Field Word
Patent Country/Region
Patent Type
Patent Status
Application Year
Inventor
LEACH protocol improvement method capable of lowering energy consumption
ActiveCN103916942ABalanced burdenAvoid failurePower managementNetwork topologiesData transmissionNetwork topology
The invention provides an LEACH protocol improvement method capable of lowering energy consumption. A basic system comprises normal nodes, cluster header nodes, forwarding nodes and a base station. The specific cycle operation steps comprise network topology determination, initialization, selection of the cluster header nodes, cluster forming, data transmission, selection of the cluster header nodes and cluster forming. According to the defects of an LEACH protocol, improvement is conducted from the aspects of selection of cluster heads, cluster forming and a data transmission mode. In selection of the cluster heads, the comprehensive influences of the energy of the nodes, the distance to the base station and density are considered, the burdens of the cluster heads are balanced, and distribution and energy consumption of the selected cluster header nodes are made balanced in a network. In cluster forming, the mode of grid clustering is used, the nodes calculate the two-dimensional values of grids where the nodes are placed by themselves, and the effectiveness of node energy is guaranteed. In data transmission mode, a routing mode with single-hop and multi-hop combined is used according to the distance of the cluster header nodes and the base station, the energy consumption of network nodes is lowered by the purpose that the energy utilization rate is highest.
Owner:ANHUI UNIVERSITY OF TECHNOLOGY AND SCIENCE
Obstacle detecting method and apparatus, device and storage medium
The present disclosure provides an obstacle detecting method and apparatus, a device and a storage medium, wherein the method comprises: obtaining a 3D point cloud collected by an unmanned vehicle during travel; projecting the 3D point cloud on a 2-dimensional grid to respectively obtain feature information of each grid; inputting the feature information of each grid into a pre-trained prediction model to respectively obtain obstacle prediction parameters of each grid; performing grid clustering according to the obstacle prediction parameters of each grid to obtain obstacle detection results. The solutions of the present disclosure can be applied to improve the accuracy of detection results.
Owner:BAIDU ONLINE NETWORK TECH (BEIJIBG) CO LTD
Method for fusing sensor grid data based on grid clustering
InactiveCN102149158AFully processedReduce energy consumptionEnergy efficient ICTNetwork topologiesSensor gridDeep level
The invention discloses a method for fusing sensor grid data based on grid clustering, which comprises the following steps: allocating tasks to all sensor nodes of each wireless sensor network, and then running an adaptive genetic algorithm based on the grid clustering in each wireless sensor network; according to perceptive data of all the sensor nodes, finding out an optimal sensor node and then finding out an optimal fusing routing with the minimum communication cost; primarily fusing data by a mobile agent along the optimal fusing routing and then sending the primarily fused result to nodes of convergent points of the network; and adopting an adaptive weighted fusion algorithm by a grid layer to carry out deep fusion on the data so as to obtain the final fused result which is providedfor a user for making decisions. The method can be applied to a sensor grid environment and is used to process the data sufficiently so as to obtain the good fused result. The grid is used for deeplyfusing the data, thus reducing energy consumption of the wireless sensor networks and prolonging the service life of sensor grids.
Owner:WUHAN UNIV OF TECH
Wireless sensor network opportunistic routing protocol based on grid clustering
InactiveCN101577668AEnergy efficient ICTData switching networksWireless sensor networkingDependability
The invention belongs to the technical field of wireless network protocols, in particular relates to an opportunistic routing method based on grid clustering in a wireless sensor network. The invention adopts a grid-type clustering method and the opportunistic routing algorithm to fully take advantages of the energy effectiveness of a clustering topology control method and the advantage of an opportunistic routing in the aspect of end-to-end throughput, thereby ensuring that the sensor network achieves effective optimization in the aspects of data throughput, transmission reliability, and the like on the premise of energy saving.
Owner:北京循天行信息技术有限公司
Multi-robot cooperative exploring and mapping method with communication distances limited under unknown environments
InactiveCN102169344AAngular velocity control input continuousAvoid timePosition/course control in two dimensionsSimulationTrajectory planning
The invention discloses a multi-robot cooperative exploring and mapping method with communication distances limited under unknown environments, belonging to the field of intelligent robot systems. The method comprises the following steps of: (1) planning local target points satisfying the constraint of the communication distances for a plurality of robots; and (2) planning motion trails from the current positions of the robots to the local target points, that is to say, planning trails. The method provided by the invention has the beneficial effects of: not only considering the factor of a linear speed, but also fully considering the influence of an angular speed on a planning time. Under the condition that the initial attitude angles of the robots are not changed, the synchronization of the motion times of the plurality of robots are kept through computing a reasonable linear speed and the motion trails of the robots are computed through solving a differential equation so that the continuous angular speed control input of all the robots is ensured, the extra time caused by the pivot turn of each robot is prevented and the plurality of robots can arrive at the target points at thesame time. Through an increment grid clustering method provided by the invention, the clustering property is kept and the computation performance is improved.
Owner:NANKAI UNIV
Grid-clustering-based RSSI (Receive Signal Strength Indicator) indoor positioning algorithm
InactiveCN108716918ARealize self-positioningNavigational calculation instrumentsCharacter and pattern recognitionCluster algorithmCentroid algorithm
The invention relates to a grid-clustering-based RSSI (Receive Signal Strength Indicator) indoor positioning algorithm which comprises the following steps: S1, placing an RFID (Radio Frequency Identification) fixed reader, randomly placing an active tag as a to-be-detected tag, and determining an RFID positioning system model; S2, repeatedly measuring the RSSI value from each reader to the to-be-detected tag at different moments, recording the measured value each time, and calculating the distance from the to-be-detected tag to each reader according to the acquired RSSI value; S3, acquiring aplurality of 'estimation tags' by using a trilateration algorithm, solving the mean of the coordinates of the 'estimation tags' as a 'target tag'; S4, defining a search region by taking the 'target tag' as a center, and dividing the region into grids of the same size; S5, screening the grid containing the most 'estimation tags' by utilizing a grid clustering algorithm, and selecting the 'estimation tags' in the grid as reference tags; S6, solving the centroid of the reference tags as the estimated value of the to-be-determined tag coordinate according to a weighted centroid algorithm.
Owner:HEFEI UNIV OF TECH
Telephone traffic distribution calculation method based on neighbor cell field intensity information and system thereof
The invention provides a telephone traffic distribution calculation method based on neighbor cell field intensity information and a system thereof. The method comprises the following steps: A, carrying out meshing on an area to be calculated of telephone traffic distribution, obtaining average filed intensity lists of different antennas received by each grid; B, carrying out clustering on grids in the area to be calculated of telephone traffic distribution, and forming primary service area grid clustering division of different antennas; C, collecting a measurement data report and total telephone traffic data generated by each antenna within a period in the area to be calculated of telephone traffic distribution; D, by utilizing the measurement data report and total telephone traffic data of each antenna, the primary service area grid clustering division, and the average filed intensity list of different antennas received by each grid, calculating telephone traffic distribution of each grid in the area to be calculated. According to the method and the system in the invention, service quality of a mobile communication network is substantially raised, and work efficiency of communication network programming and optimizing personnel are raised.
Owner:GRADUATE SCHOOL OF THE CHINESE ACAD OF SCI GSCAS
On-board LiDAR point cloud road information extraction method and device
PendingCN108919295AQuick extractionReduce computing timeElectromagnetic wave reradiationHigh elevationPoint cloud
The invention provides an on-board LiDAR point cloud road information extraction method and device. The method comprises the following steps that point cloud data of a to-be-detected road is filteredto obtain ground point cloud data; a two-dimensional net is established for ground point cloud data; first average elevation value for each grid, a highest elevation, a lowest elevation for and secondaverage elevation value of all adjacent grids are determined, existence of road point grids in all the adjacent grids is determined according to values; when the road point grids exist, grid clustering is carried out for all road point grids to determine road point grid clusters; and according to the size of each road point grid cluster, whether the point cloud data in the road point grid clusterare road point cloud data is determined. According to the technical scheme, a standard spatial grid is established for the point cloud, location of the road is determined by the spatial distributioncharacteristics and the relationship between elevation differences; and the grids with roads are determined according to the grid cluster growth mode to achieve the aim of road extraction.
Owner:国网电力空间技术有限公司 +1
Grid clustering algorithm based on density peak value
InactiveCN107491779AAvoid failureSuitable for handlingCharacter and pattern recognitionCluster algorithmData set
The invention requests to protect a grid clustering algorithm based on a density peak value, and can efficiently processing large-scale data. The algorithm comprises the following steps that: firstly, pelletizing an N-dimensional space into nonintersecting rectangular grid unit, and then, carrying out statistics on the information of unit space; utilizing a thought that a density peak value clustering is used for searching a center point to determine a center unit, i.e., surrounding the center grid unit by certain data units with low local density, and forming a large distance with the grid unit with high self local density; and finally, combining the grid units near the center grid unit so as to obtain a clustering result. A situation experiment result on an UCI (University of CaliforniaIrvine) artificial data set indicates that the algorithm can quickly obtain a clustering center, the clustering problem of large-scale data can be effectively processed, and the algorithm is high in efficiency. Compared with an original density peak value clustering algorithm, the algorithm is characterized in that time loss on different datasets is lowered by 10-100 times and accuracy loss is maintained at 5-8%.
Owner:CHONGQING UNIV OF POSTS & TELECOMM
System and method for mining workplace-residence position tag based on mobile communication signaling big data
ActiveCN106547894AReduce collection dimensionsGood clustering effectRelational databasesSpecial data processing applicationsResidenceUser - individual
The invention discloses a system and a method for mining a workplace-residence position tag based on mobile communication signaling big data. The key point of the technical scheme is as follows: the system comprises a user individual activity sequence establishment unit used for establishing user individual activity sequences, a grid generation unit used for dividing position information of a cell into uniform grids, a grid cluster analysis calculation unit used for calculating occupied dense grid clusters in appointed time frame by calling a grid cluster analysis calculation algorithm, a density cluster analysis calculation unit used for calculating mass centers of the occupied dense grid clusters by calling a density cluster analysis calculation algorithm, and a workplace-residence position tag generation unit for generating the workplace-residence position tag of the user. The system and the method have the advantages as follows: 1) any assumption on the user behavior sequence data distribution is not required and the obtained result through analysis is not related to data record processing sequence, so that relatively high objective degree is achieved; 2) sub spaces with cluster probability are found automatically; and 3) the complexity of data ETL is lowered.
Owner:浙江夏农信息技术有限公司
Grid clustering analysis-based violence behavior detection method
The invention discloses a grid clustering analysis-based violence behavior detection method. The method comprises the following steps of: S1, reading a video streaming from camera equipment or an existing video file, and obtaining source picture frames in the video streaming; S2, preprocessing the source picture frames; S3, detecting human bodies in the preprocessed source picture frames and framing out the detected human bodies; S4, obtaining optical flow feature points of the source picture frame and carrying out optical flow tracing on the optical flow feature points; S5, carrying out clustering analysis on the optical flow feature points to obtain moving objects in the image; S5, analyzing moving conditions of the moving objects; and S7, carrying out statistic on a degree of polymerization change trend of the moving objects in continuous image frames so as to judge the detection of violence incidents. According to the method, the degree of polymerization change trend among a plurality of moving objects is calculated through video image information, and human body detection is carried out to judge whether violence incidents occur or not.
Owner:GUANGZHOU UNIVERSITY
A Spark cluster parallel computing-based traffic jam point discovery method
ActiveCN109739585AClustering fastImprove processing efficiencyData processing applicationsCharacter and pattern recognitionCluster algorithmGrid density
The invention discloses a traffic jam point discovery method based on Spark cluster parallel computing. The invention discloses a trajectory big data mining method, relates to the technical field of trajectory big data mining, solves the technical problem of how to quickly cluster massive trajectory data and find a traffic congestion source of an urban hot region, and comprises the following steps: (1) preprocessing the massive data, including complementing errors between trajectory points and eliminating trajectory point redundancy in a certain region for a period of time; (2) adopting a grid-means clustering algorithm to carry out clustering to obtain a plurality of target data samples; (3) clustering by adopting a neighborhood maximum density grid clustering algorithm to obtain an urbanhot traffic road network model; and (4) calculating the adjacent grid density difference by adopting a neighborhood density difference algorithm to obtain a traffic jam source, and storing the obtained result in a Spark memory. According to the method, mass data can be quickly clustered to obtain an urban traffic network model, and quick discovery of a traffic jam source region is realized.
Owner:GUANGXI TRANSPORTATION SCI & TECH GRP CO LTD +1
Variational Error Correction System and Method of Grid Generation
A system and method for automatically generating a computation mesh for use with an analytical tool, the computation mesh having a plurality of ξ-grid lines and η-grid lines intersecting at grid points positioned with respect to an inner boundary and an outer boundary. The system and method include one or more mesh equations having one or more source terms that include: a grid clustering component based on a Jacobian scaling parameter, a source decay parameter, and one or more first point distance parameters, and a cell shape modifying source component based on one or more source parameters selected from the group consisting of a smoothing source parameter, an area source parameter, an orthagonality source parameter, and any combinations thereof.
Owner:SAMSUNG ELECTRONICS CO LTD +1
Wireless rechargeable sensor network grid clustering routing method
ActiveCN108770028AExtend working lifeSolve the problem of energy imbalanceNetwork topologiesData switching networksData transmission timeSensor node
The invention discloses a wireless rechargeable sensor network grid clustering routing method. The wireless rechargeable sensor network grid clustering routing method comprises the steps that a virtual cellular grid is used for dividing the sensor network, and the sensor nodes in each virtual cellular grid form a cluster, and the charging path of a charging device according to the virtual cellulargrid division result; the charging device is used for executing the charging task from the service station S along the charging path, a cluster node in each virtual cellular grid is calculated according to the charging task executed by the charging device; according to the sensor node, the charging device and the cluster node in each virtual cellular grid, so that the data transmission flow between the sensor nodes in the sensor network is guaranteed. According to the invention, the problem that the energy of the sensor nodes is unbalanced is effectively solved, the data transmission time delay is reduced, and the service life of the wireless rechargeable sensor network is prolonged.
Owner:HEFEI UNIV OF TECH
Grid division processing method and device based on city map and computer equipment
ActiveCN110569321AEfficient identificationClimate change adaptationGeographical information databasesComputer scienceArea type
The invention relates to a grid division processing method and device based on a city map, computer equipment and a storage medium in the field of artificial intelligence. The method comprises the following steps: acquiring a city identifier and a corresponding city map, and dividing the city map to obtain a plurality of regional grids; acquiring corresponding user information according to the city identifier; dividing each user into a corresponding regional grid according to the user information; wherein the user information comprises geographic coordinates and uploading time; identifying thearea type of each area grid by utilizing the geographic coordinates of each area grid in the preset time period and the corresponding uploading time; and acquiring a plurality of regional grids in apreset range of the city map, performing regional grid clustering according to the distances among the regional grids and the regional types to obtain an activity region of the user, and marking the activity region in the city map. According to the method, the city map is divided, so that the user activity area can be quickly and effectively identified.
Owner:PING AN TECH (SHENZHEN) CO LTD
Rapid night vehicle detection method applied to self-adaptive high beam
ActiveCN110084111AEliminate false positivesGuaranteed real-timeCharacter and pattern recognitionData informationVehicle detection
The invention discloses a rapid night vehicle detection method applied to a self-adaptive high beam, and the method comprises the steps: step 1, enabling an image collection module to collect a road traffic image in front of a vehicle, and transmitting image data information to an image processing module; step 2, processing the image data information by an image processing module, and judging a suspected vehicle lamp region by adopting a grid clustering algorithm; step 3, determining a halo range of a suspected vehicle lamp region by adopting a corrosion algorithm, calculating a halo color through a rapid algorithm, and judging a headlamp and a tail lamp; step 4, conducting pairing according to the geometrical relationship, recognizing vehicles, calculating vehicle coordinate position information and achieving night vehicle detection; and step 5, enabling a data transmission module to transmit the vehicle coordinate information calculated by the image processing module to the high beamcontrol module. The final vehicle lamp information obtained through image processing can serve as the control basis of the self-adaptive high beam lamp and can also provide support for other modulesneeding the vehicle lamp information.
Owner:JIANGSU UNIV
Dynamic grid generation method, generation device, polymerization method and polymerization device
ActiveCN104933437AMeet real-time requirementsAvoid the problem of large aggregation deviationCharacter and pattern recognitionCluster algorithmReference Region
The invention discloses a dynamic grid generation method. The dynamic grid generation method comprises the following steps: taking a sealed region formed by maximum and minimum longitude and latitude lines of a current display region as a reference region of the current display region; finding out a reference point closest to any point of the reference region as a closest reference point, wherein the closest reference point is found from a pre-stored reference point database or is instantly generated from the known reference points; and taking the closest reference point as a starting point for extending in the longitude and latitude directions to generate a minimum dynamic grid which is composed of a plurality of unit grids and completely covers the current display region. The invention further discloses a dynamic grid generation device, and a polymerization method and device based on the dynamic grid. With the adoption of the embodiment of the invention, the problems in a grid clustering algorithm that a lot of data need to be stored, the data processing speed is low and the polymerization errors are great can be effectively solved.
Owner:GCI SCI & TECH
An improvement method of leach protocol for reducing power consumption
ActiveCN103916942BBalanced burdenAvoid failurePower managementNetwork topologiesData transmissionNetwork topology
Owner:ANHUI POLYTECHNIC UNIV
Dynamic grid generating method, generating apparatus, clustering method and clustering apparatus
ActiveCN105046267AAvoid generatingMeet real-time requirementsCharacter and pattern recognitionCluster algorithmLongitude
The invention discloses a dynamic grid generating method. The method comprises the following steps of making an enclosed area formed by the largest and smallest latitude lines and longitude lines on a current display area serve as the reference area of the current display area; finding out a reference point nearest to any point on the reference area as a nearest reference point; judging whether to generate a current display area reference point according to the position relationship of the nearest reference point and the reference area; if yes, then extending towards the latitude and longitude directions with the current display area reference point as a starting point to generate a minimum dynamic grid composed of a plurality of unit grids and fully covering the current display area; and if no, then creating a minimum dynamic grid with the nearest reference point as the starting point. The invention further discloses a dynamic grid generating apparatus, a clustering method and a clustering apparatus based on the dynamic grid. By means of the method, the problems of a grid-clustering algorithm which requires storage of large amounts of data and results in a low data processing speed and great clustering errors are solved.
Owner:GCI SCI & TECH
Dynamic clustering algorithm for geographic grids
InactiveCN104021274ACoarse and fine-grained free controlIncrease flexibilitySpecial data processing applicationsCluster algorithmGranularity
The invention discloses a dynamic clustering algorithm for geographic grids. The method includes the steps that firstly, the maximum longitude and latitude and the minimum longitude and latitude are found out in an area, and then according to the step length, grid division is performed on the area between the maximum longitude and latitude and the minimum longitude and latitude; serial numbers of the grids where all points are located are calculated, the points in the same grid are clustered, and the gravity center of clustering is calculated; then the grids are moved in the vertical direction and the horizontal direction, the moving lengths are kept uniform, the frequencies of moving in the directions mutually symmetrical are kept uniform, the sequence of the moving directions is not limited, after moving each time, the points, meeting clustering conditions, in the grids are clustered, and all the clustered points form a final clustered result. According to the method, the problems that a traditional clustering algorithm based on the grids is low in precision and efficiency are solved, the grids can be drawn dynamically through the method, the granularity can be freely controlled, flexibility is high, and the speed is high.
Owner:FENGHUO COMM SCI & TECH CO LTD
Multi-hypothesis multi-target track initiation method based on grid clustering
PendingCN112098992ASolve falseSolve the problem of low initial accuracy of multi-target trackCharacter and pattern recognitionRadio wave reradiation/reflectionHigh densityMultiple hypothesis
The invention provides a multi-hypothesis multi-target track initiation method based on grid clustering. The multi-hypothesis multi-target track initiation method comprises the steps of obtaining a trace point set and mapping the trace point set into a grid; determining boundary points of the current high-density grid; forming a trace point cluster based on boundary points of the high-density grid; performing clustering processing on each trace point cluster to generate a cluster; establishing an association hypothesis of a target and measurement in the cluster; and obtaining an optimal hypothesis according to the hypothesis probability obtained through calculation, calculating track scores, sorting the track scores from high to low, deleting low-score tracks through backtracking so as toconfirm track generation, and updating target state estimation of the tracks. According to the method, a plurality of target tracks can be initiated, the problem of multiple false tracks in a high-density clutter environment is solved, and engineering application under a high-density clutter condition is facilitated.
Owner:DALIAN MARITIME UNIVERSITY
Method for intelligently making peak shaving and load shifting strategy for power customers
InactiveCN106204321AAvoid disadvantages that are not realisticPracticalData processing applicationsCharacter and pattern recognitionCluster algorithmCurve shape
The invention discloses a method for intelligently making a peak shaving and load shifting strategy for power customers, and the method comprises the steps: carrying out the clustering of load curves of a regional power grid in a certain time through employing a two-step clustering algorithm, and obtaining a regional power grid clustering result, wherein the regional power grid clustering result comprises a clustering center curve and clustering details; carrying out the dividing of the peak and valley of the load curves of the regional power grid, and carrying out the matching of a power customer curve at a corresponding date through combing with the regional power grid clustering result; carrying out the clustering of the power customer load curve of a certain type of regional power grids in the same period at the peak and valley through employing the two-step clustering algorithm, obtaining the clustering result of the power customer, wherein the clustering result comprises a clustering center curve and clustering details; and constructing a peak shaving and load shifting index of the power customer according to the normalized mean value of the power customer clustering center curves of the regional power grid and the similarity between the regional power grid and the corresponding power customer clustering center curve. The method is high in practicality, and irons out a defect that the recommended peak shaving and load shifting strategy of the power customer does not accord with the actual condition because only the curve shape or load absolute value is considered.
Owner:MERIT DATA CO LTD
A multi-extension target tracking method under space-time neighbor target detection and grid clustering measurement division
ActiveCN109671096AImprove accuracyAvoid falling intoImage analysisCharacter and pattern recognitionGrid densitySpacetime
Owner:NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
Obstacle recognition method based on 3D point cloud data and computer equipment
ActiveCN111144228AHigh precisionGuaranteed real-timeInternal combustion piston enginesThree-dimensional object recognitionPoint cloudEngineering
The invention designs an obstacle recognition method based on 3D point cloud data and computer equipment. The method comprises the steps of obtaining 3D point cloud data, and mapping the 3D point cloud data to a plane to obtain a grid map; obtaining an obstacle center area from the grid map by using a grid clustering method, and obtaining an obstacle reference point according to the obstacle center area; screening points in grid units outside the central area of the obstacle in the grid map by utilizing the obstacle reference point to obtain an obstacle edge area; and determining obstacle information according to the obstacle center area and the obstacle edge area. By adopting the method, the real-time performance is ensured by acquiring the central area of the obstacle through the grid clustering method, and in addition, the areas except the central area of the obstacle are clustered point by point, so that the phenomena of under-segmentation and over-segmentation are greatly reduced,and the accuracy of acquiring obstacle information is effectively improved.
Owner:SHANDONG CHAOYUE DATA CONTROL ELECTRONICS CO LTD
Video image stabilization motion estimation method based on reference frame optimization and foreground and background separation
ActiveCN111598918AFix poor qualityCalculation speedTelevision system detailsImage enhancementPattern recognitionCluster algorithm
The invention discloses a video image stabilization motion estimation method based on reference frame optimization and foreground and background separation, which is used for solving the problem thatthe effect after image stabilization processing is influenced by inaccurate motion vector estimation. The method comprises steps of firstly, carrying out reference frame selection optimization by taking adjacent frame priority as a principle, and then carrying out clustering and preliminary screening on feature points in video frames in a grid clustering and density clustering algorithm fusion mode; solving an optimal homography matrix by using a random sampling consistency algorithm, and solving the distance between the feature point pairs by combining perspective projection transformation; and removing the feature point pairs which do not meet a preset condition according to a distance criterion to obtain purified feature point pairs; and finally, using the obtained accurate background feature point pairs for calculating a global motion vector. According to the video image stabilization motion estimation method disclosed by the invention, the influence of the foreground on motion estimation is effectively removed, the estimated global motion vector precision is improved, the image stabilization restoration effect is improved, and the method can be widely applied to image stabilization restoration of videos shot by different shooting devices.
Owner:JIANGSU UNIV
Common-mode antenna feeder optimization method and system based on adaboost weighting and third-order clustering
The embodiment of the invention provides a common-mode antenna feeder optimization method and system based on adaboost weighting and third-order clustering. The method comprises the steps of: fusing drive test data, first data and position information in any one network, and carrying out grid clustering on the fused data so as to obtain a data set of any one network; respectively determining an optimal weight corresponding to the data set of any network by adopting an AdaBoost algorithm according to the respectively set initial weights corresponding to the data set of any network, and obtaining a second data set according to the optimal weight corresponding to the data set of any network and the data set of any network; selecting second sampling points of which RSRP or SINR in the second data set is smaller than a preset threshold value, and clustering each sampling point in the second sampling points with the position information to generate a difference geographical position clustering set; and calculating included angles between the horizontal lobe normal of an antenna in a first common-mode cell and the difference point geographic position clustering set and between the vertical lobe normal of the antenna in the first common-mode cell and the difference point geographic position clustering set according to the difference point geographic position clustering set and the antenna feed value of the first common-mode cell.
Owner:SHANXI CHINA MOBILE COMM CORP +1
Parallel clustering method for processing large geographical grid data
InactiveCN105045934AClustering results are fastClustering results are quickly obtainedGeographical information databasesSpecial data processing applicationsData fileMachine learning
The invention relates to a parallel clustering method, in particular to a parallel clustering method for processing large geographical grid data and belongs to the field of parallel clustering for processing the large geographical grid data. The problems that because geographical grids are quite enormous and exceed a stand-alone loading limit, a system can not operate or operation efficiency is quite low, and all progress computing results interchange mutually when multiple computers perform parallel clustering are solved. The method includes the steps that step1, the number of nodes is calculated, and each computing progress is numbered; step2, the data are transmitted to computing progresses, and the numbers of the computing progresses are IDs; step3, M sets of clustering solution initial values are generated; step4, a clustering vector central table is sent to the computing progresses; step5, a management progress controls an iteration solution progress; step6, content of the row, with the highest value, of a field 4 is sent to all the computing progresses; step7, grid clustering results are written into a geographical grid data file. In this way, the parallel clustering method for processing the large geographical grid data is implemented through the steps.
Owner:CHANGCHUN INST OF TECH
Improved method for solving fan power curve parameter model based on genetic algorithm
InactiveCN105069192AIncrease credibilityIncrease time complexitySpecial data processing applicationsElectricityOriginal data
The invention discloses an improved method for solving a fan power curve parameter model based on a genetic algorithm. According to the method, each parameter in the fan power curve parameter model is determined through fan operation data in an operational process of wind power units. But in a process for solving the parameters of the model by using the genetic algorithm, the fitness of all individuals in a population is calculated in each iterative process, and when the data volume of the fan operation data is increased, the calculation amount of a fitness function and an evaluation function of the population is increased accordingly and the space complexity and time complexity of a program are also increased. Therefore, the fan operation data is subjected to grid-based clustering and weight assignment first and then each parameter in the parameter model is determined by applying the genetic algorithm, in the method. By clustering the fan operation data, the increment of the calculation amount of the fitness function and the evaluation function caused by the increment of the data volume of the fan operation data can be avoided; and by assigning weights to clustering points, the model can adapt to most original data points and the credibility of the model is enhanced.
Owner:HEBEI UNIV OF TECH
Optimized method of variable k coverage for two-dimensional intrusion monitoring region
ActiveCN105072622AEffective monitoringGive full play to the role of nodesNetwork topologiesHigh level techniquesCluster algorithmSensor node
The invention discloses an optimized method of variable k coverage for a two-dimensional intrusion monitoring region. The method comprises the following steps: step (1), abstracting an intrusion object as a point and constructing a two-dimensional monitoring region coverage model of single point intrusion; and step (2), meshing a two-dimensional monitoring region according to the two-dimensional monitoring region coverage model of single point intrusion and a grid clustering algorithm, performing clustering according to the coverage of each grid cell after meshing, movably deploying sensor nodes in the two-dimensional monitoring region according to the comparison of the current coverage with the desired coverage, and finally realizing the variable k coverage of the two-dimensional monitoring region. According to the method, the nodes are re-deployed to realize flexibly variable coverage of different regions at different times; in the case of limited sensor nodes, the effects of the nodes are developed thoroughly to ensure multiple coverage of a key region and also satisfy the coverage requirement of a common region; as a result, effective monitoring on the intrusion object can be realized at the cost of consuming less energy.
Owner:SHANDONG NORMAL UNIV
Clustering method based on adjacent grid search
PendingCN110781943AEfficient identificationCharacter and pattern recognitionOriginal dataGrid operator
The invention discloses a clustering method based on an adjacent grid search strategy, and the method comprises the steps: firstly carrying out grid division of original data: enabling an original data set to be divided into a limited number of cells through a multi-dimensional space grid, and carrying out the denoising processing when necessary; secondly, performing grid clustering on the divided data: processing the denoised grids by utilizing a halo threshold value, and dividing the denoised grids into halo cell elements and core cell elements; establishing an adjacent grid operator for quickly searching an adjacent cell element of one cell element; achieving a clustering process through two steps of core cell element clustering and halo cell element division, dividing all core cell elements into a plurality of class clusters through a traversal algorithm, and dividing halo cell elements into existing class clusters based on cell element distances; and finally, clustering optimization is carried out according to data characteristics and user requirements. Compared with the prior art, the method has the advantages that a new clustering method can be provided for rapidly increasing the dimension of the sample set, and class clusters with complex boundary shapes can be effectively identified.
Owner:TIANJIN CHENGJIAN UNIV
Who we serve
- R&D Engineer
- R&D Manager
- IP Professional
Why Patsnap Eureka
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com